Edge Detection Based on Spiking Neural Network Model

Inspired by the behaviour of biological receptive fields and the human visual system, a network model based on spiking neurons is proposed to detect edges in a visual image. The structure and the properties of the network are detailed in this paper. Simulation results show that the network based on spiking neurons is able to perform edge detection within a time interval of 100 ms. This processing time is consistent with the human visual system. A firing rate map recorded in the simulation is comparable to Sobel and Canny edge graphics. In addition, the network can separate different edges using synapse plasticity, and the network provides an attention mechanism in which edges in an attention area can be enhanced.

• Type: Conference
• Year: 2007
• Where: ICIC
• Authors: Qingxiang Wu, T. Martin McGinnity, Liam P. Maguire, Ammar Belatreche, Brendan P. Glackin
• Keywords: Biological Receptive Fields, Human Visual System, ICIC 2007, Network Model